9. Facilitating Effective User Navigation through Website Structure Improvement

Abstract:

Designing well-structured websites to facilitate effective user navigation has long been a challenge. A primary reason is that the web developers understanding of how a website should be structured can be considerably different from that of the users. While various methods have been proposed to relink webpages to improve navigability using user navigation data, the completely reorganized new structure can be highly unpredictable, and the cost of disorienting users after the changes remains unanalyzed. This paper addresses how to improve a website without introducing substantial changes.

Specifically, we propose a mathematical programming model to improve the user navigation on a website while minimizing alterations to its current structure. Results from extensive tests conducted on a publicly available real data set indicate that our model not only significantly improves the user navigation with very few changes, but also can be effectively solved. In addition, we define two evaluation metrics and use them to assess the performance of the improved website using the real data set. Evaluation results confirm that the user navigation on the improved structure is indeed greatly enhanced. More interestingly, we find that heavily disoriented users are more likely to benefit from the improved structure than the less disoriented users.

Existing System:

A primary cause of poor website design is that the web developers understanding of how a website should be structured can be considerably different from those of the users. Such differences result in cases where users cannot easily locate the desired information in a website. This problem is difficult to avoid because when creating a website, web developers may not have a clear understanding of users preferences and can only organize pages based on their own judgments. However, the measure of website effectiveness should be the satisfaction of the users rather than that of the developers. Thus, Web pages should be organized in a way that generally matches the users model of how pages should be organized.

Proposed System:

We propose a mathematical programming model to improve the user navigation on a website while minimizing alterations to its current structure. Results from extensive tests conducted on a publicly available real data set indicate that our model not only significantly improves the user navigation with very few changes, but also can be effectively solved. In addition, we define two evaluation metrics and use them to assess the performance of the improved website using the real data set. Evaluation results confirm that the user navigation on the improved structure is indeed greatly enhanced. More interestingly, we find that heavily disoriented users are more likely to benefit from the improved structure than the less disoriented users.

Modules:

1. Web personalization Web personalization is the process of tailoring webpages to the needs of specific users using the information of the users navigational behavior and profile data. Perkowitz and Etzioni describe an approach that automatically synthesizes index pages which contain links to pages pertaining to particular topics based on the co-occurrence frequency of pages in user traversals, to facilitate user navigation. The methods proposed by Mobasher et al. and Yan et al. create clusters of users profiles from weblogs and then dynamically generate links for users who are classified into different categories based on their access patterns.

2. Web transformation Web transformation, on the other hand, involves changing the structure of a website to facilitate the navigation for a large set of users instead of personalizing pages for individual users. Fu et al. describe an approach to reorganize web pages so as to provide users with their desired information in fewer clicks. However, this approach considers only local structures in a website rather than the site as a whole, so the new structure may not be necessarily optimal. Gupta et al. propose a heuristic method based on simulated annealing to relink web pages to improve navigability. This method makes use of the aggregate user preference data and can be used to improve the link structure in websites for both wired and wireless devices.

3. Maximal Forward Reference We use backtracks to identify the paths that a user has traversed, where a backtrack is defined as a users revisit to a previously browsed page. The intuition is that users will backtrack if they do not find the page where they expect it . Thus, a path is defined as a sequence of pages visited by a user without backtracking, a concept that is similar to the maximal forward reference defined in Chen et al. Essentially, each backtracking point is the end of a path. Hence, the more paths a user has traversed to reach the target, the more discrepant the site structure is from the users expectation.

4. Mini Sessions Recall that a mini session is relevant only if its length is larger than the corresponding path threshold. Consequently, only relevant mini sessions need to be considered for improvement and this leads to a large number of irrelevant mini sessions (denoted as TI ) being eliminated from consideration in our MP model.

5. Out-Degree ThresholdWeb pages can be generally classified into two categories : index pages and content pages. An index page is designed to help users better navigate and could include many links, while a content page contains information users are interested in and should not have many links. Thus, the out-degree threshold for a page is highly dependent on the purpose of the page and the website. Typically, the out degree threshold for index pages should be larger than that for content pages.H/W System Configuration:

Processor-Intel Core 2 Duo RAM-1 GB(min) Hard Disk-300 GB

S/W System Configuration:

Operating System:Windows-XP Application Server:Apache Tomcat 5.0/6.X Front End:HTML, Java 6.0, JSP Scripts:JavaScript. Server side Script:Java Server Pages. Database:Mysql 5.0 Database Connectivity:JDBC.